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/ESA_selects_Harmony_as_tenth_Earth_Explorer_mission ) The candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via
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includes the opportunity for three weeks of training in higher education teaching and learning. The postdoctoral fellow will: Develop and maintain harmonized satellite time-series datasets (Landsat and
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/ESA_selects_Harmony_as_tenth_Earth_Explorer_mission ) The candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via
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for Transportation (VITA ) is looking for a postdoctoral researcher in the area of Generative AI. VITA research interests lie at the intersection of Computer Vision, Machine Learning (Deep Learning), and Human-Robot
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conferences. About You You will be educated to doctoral level in Remote Sensing, Geography, Geoinformatics, Computer Science, Artificial Intelligence, Machine Learning or a related discipline. You will have
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, with a strong interest in the integration of geospatial Artificial Intelligence (AI) and machine learning. Are you enthusiastic about the chance to combine research in Remote Sensing and AI with teaching
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operational forest inventory methods. The project combines unmanned aerial laser scanning (ULS), terrestrial and mobile laser scanning (TLS/MLS), statistical calibration-transfer, and machine learning
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conduct world-class applied research. We change and make a difference. Do you want to become one of us? This postdoctoral position is part of the newly funded KKS Synergy project WorkFlex+ which focuses
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National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | 18 days ago
to advance use of foundation models for Earth Science research and applications, including fine-tuning experiments Use of remote sensing, models, and/or machine learning to further our understanding
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or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the